Bishop: Sparsified Bundling Spiking Transformers on Heterogeneous Cores with Error-Constrained Pruning | Paper Citation Record

Observation 4cb09e0d-42b3-4238-9e19-1e3e3612a5d5 · outbound

This paper cites A low power, fully event-based gesture recognition system,.

Bishop: Sparsified Bundling Spiking Transformers on Heterogeneous Cores with Error-Constrained Pruning A low power, fully event-based gesture recognition system,

Reference 1

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Observation da75ae7b-e846-4fa5-ae2f-08b9f8f81b06 · outbound

This paper cites Spikingbert: Distilling bert to train spiking language models using implicit differentiation,.

Bishop: Sparsified Bundling Spiking Transformers on Heterogeneous Cores with Error-Constrained Pruning Spikingbert: Distilling bert to train spiking language models using implicit differentiation,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:45:58.953367Z

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This paper cites Cacti 7: New tools for interconnect exploration in innovative off-chip memories,.

Bishop: Sparsified Bundling Spiking Transformers on Heterogeneous Cores with Error-Constrained Pruning Cacti 7: New tools for interconnect exploration in innovative off-chip memories,

Reference 3

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Observation c3a79e8b-2a09-4952-b7e4-ea996abd14ff · outbound

This paper cites Pruning of Deep Spiking Neural Networks through Gradient Rewiring.

Bishop: Sparsified Bundling Spiking Transformers on Heterogeneous Cores with Error-Constrained Pruning Pruning of Deep Spiking Neural Networks through Gradient Rewiring

Reference 4

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Observation 4708f1aa-37a0-4c37-a70c-d25d574732c0 · outbound

This paper cites Towards ultra low latency spiking neural networks for vision and sequential tasks using temporal pruning,.

Bishop: Sparsified Bundling Spiking Transformers on Heterogeneous Cores with Error-Constrained Pruning Towards ultra low latency spiking neural networks for vision and sequential tasks using temporal pruning,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:45:58.942326Z

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Observation 2a276f4b-1852-465f-9619-ffc275f6255e · outbound

This paper cites Transformer-xl: Attentive language models beyond a fixed-length context,.

Bishop: Sparsified Bundling Spiking Transformers on Heterogeneous Cores with Error-Constrained Pruning Transformer-xl: Attentive language models beyond a fixed-length context,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:45:58.930572Z

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Observation 8cc0ee2b-583b-4386-9de7-76d980bbc377 · outbound

This paper cites Flashattention: Fast and memory- efficient exact attention with io-awareness,.

Bishop: Sparsified Bundling Spiking Transformers on Heterogeneous Cores with Error-Constrained Pruning Flashattention: Fast and memory- efficient exact attention with io-awareness,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:45:58.920057Z

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Observation 2c85bf3e-1fed-4408-8c1d-a3d1291928d5 · outbound

This paper cites ViTALiTy: Unifying low- rank and sparse approximation for vision transformer acceleration with a linear taylor attention,.

Bishop: Sparsified Bundling Spiking Transformers on Heterogeneous Cores with Error-Constrained Pruning ViTALiTy: Unifying low- rank and sparse approximation for vision transformer acceleration with a linear taylor attention,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:45:58.908410Z

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Observation f83917a5-6765-4c92-a635-aae955ee52e5 · outbound

This paper cites Loihi: A neuromorphic manycore processor with on-chip learning,.

Bishop: Sparsified Bundling Spiking Transformers on Heterogeneous Cores with Error-Constrained Pruning Loihi: A neuromorphic manycore processor with on-chip learning,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:45:58.892998Z

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Observation 123a1d18-18c9-4e04-a0d6-9b8d41735969 · outbound

This paper cites A neural attention model for speech command recognition.

Bishop: Sparsified Bundling Spiking Transformers on Heterogeneous Cores with Error-Constrained Pruning A neural attention model for speech command recognition

Reference 10

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Observation d32307f1-bd34-49f3-a1f8-7459168becf4 · outbound

This paper cites Truenorth: Accelerating from zero to 64 million neurons in 10 years,.

Bishop: Sparsified Bundling Spiking Transformers on Heterogeneous Cores with Error-Constrained Pruning Truenorth: Accelerating from zero to 64 million neurons in 10 years,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:45:58.879667Z

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Observation c4422a24-0fc6-4c6c-adbc-636594853f58 · outbound

This paper cites Imagenet: A large-scale hierarchical image database,.

Bishop: Sparsified Bundling Spiking Transformers on Heterogeneous Cores with Error-Constrained Pruning Imagenet: A large-scale hierarchical image database,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:45:58.867755Z

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Observation b85fbbb5-d5bf-4fc7-8d73-5c92e3d935e3 · outbound

This paper cites Compre- hensive snn compression using admm optimization and activity regularization,.

Bishop: Sparsified Bundling Spiking Transformers on Heterogeneous Cores with Error-Constrained Pruning Compre- hensive snn compression using admm optimization and activity regularization,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:45:58.855788Z

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Observation f25e8d0d-8eaf-4d73-955f-c243f12b2f56 · outbound

This paper cites Comprehensive snn compression using admm optimization and activity regularization,.

Bishop: Sparsified Bundling Spiking Transformers on Heterogeneous Cores with Error-Constrained Pruning Comprehensive snn compression using admm optimization and activity regularization,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:45:58.843566Z

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Observation d8e1daac-ed44-4657-9617-462f99132446 · outbound

This paper cites Temporal Efficient Training of Spiking Neural Network via Gradient Re-weighting.

Bishop: Sparsified Bundling Spiking Transformers on Heterogeneous Cores with Error-Constrained Pruning Temporal Efficient Training of Spiking Neural Network via Gradient Re-weighting

Reference 15

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Observation 2db99df1-22b0-41b8-ba2c-974731683271 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Bishop: Sparsified Bundling Spiking Transformers on Heterogeneous Cores with Error-Constrained Pruning An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 16

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Observation d0c494b5-63ab-4a4b-bdb5-92b8c2eb7c51 · outbound

This paper cites Adaptable butterfly accelerator for attention-based NNs via hardware and algorithm co-design,.

Bishop: Sparsified Bundling Spiking Transformers on Heterogeneous Cores with Error-Constrained Pruning Adaptable butterfly accelerator for attention-based NNs via hardware and algorithm co-design,

Reference 17

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Observation 94f29603-dd97-414f-a1f2-7e043a0278c4 · outbound

This paper cites Taskfusion: An efficient transfer learning architecture with dual delta sparsity for multi-task natural language processing,.

Bishop: Sparsified Bundling Spiking Transformers on Heterogeneous Cores with Error-Constrained Pruning Taskfusion: An efficient transfer learning architecture with dual delta sparsity for multi-task natural language processing,

Reference 18

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Observation 8df00dc4-97f0-4dfc-a4c5-ab294b57dad6 · outbound

This paper cites Deep residual learning in spiking neural networks,.

Bishop: Sparsified Bundling Spiking Transformers on Heterogeneous Cores with Error-Constrained Pruning Deep residual learning in spiking neural networks,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:45:58.831588Z

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Observation 2261d2e9-5777-47ec-8e02-df7fced1e47a · outbound

This paper cites Gerstner and W.

Bishop: Sparsified Bundling Spiking Transformers on Heterogeneous Cores with Error-Constrained Pruning Gerstner and W

Reference 20

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Observation 7ba54f8a-02ad-4ec3-9f66-1f11a4312033 · outbound

This paper cites Single-word speech recognition with convolutional neural networks on raw waveforms,.

Bishop: Sparsified Bundling Spiking Transformers on Heterogeneous Cores with Error-Constrained Pruning Single-word speech recognition with convolutional neural networks on raw waveforms,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:45:58.811153Z

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This paper cites 20.5 c-transformer: A 2.6-18.1j/token homogeneous dnn-transformer/spiking-transformer processor with big-little network and implicit weight generation for large language models,.

Bishop: Sparsified Bundling Spiking Transformers on Heterogeneous Cores with Error-Constrained Pruning 20.5 c-transformer: A 2.6-18.1j/token homogeneous dnn-transformer/spiking-transformer processor with big-little network and implicit weight generation for large language models,

Reference 22

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Observation f060361f-3a0a-47f4-8867-87431be72837 · outbound

This paper cites Dynamic spike bundling for energy-efficient spiking neural networks,.

Bishop: Sparsified Bundling Spiking Transformers on Heterogeneous Cores with Error-Constrained Pruning Dynamic spike bundling for energy-efficient spiking neural networks,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:45:58.787685Z

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Observation 6457da8b-4b47-47d5-bc66-62badf721c92 · outbound

This paper cites Enabling spike-based backpropagation for training deep neural network architectures,.

Bishop: Sparsified Bundling Spiking Transformers on Heterogeneous Cores with Error-Constrained Pruning Enabling spike-based backpropagation for training deep neural network architectures,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:45:58.776195Z

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Observation 4c66bf29-9178-4fad-adf8-dc99d4e7a3bb · outbound

This paper cites Flexon: A flexible digital neuron for efficient spiking neural network simulations,.

Bishop: Sparsified Bundling Spiking Transformers on Heterogeneous Cores with Error-Constrained Pruning Flexon: A flexible digital neuron for efficient spiking neural network simulations,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:45:58.765868Z

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Observation 1393aa08-89ef-4608-84ac-d87740a32ad3 · outbound

This paper cites Reconfigurable dataflow optimization for spatiotemporal spiking neural computation on systolic array accelerators,.

Bishop: Sparsified Bundling Spiking Transformers on Heterogeneous Cores with Error-Constrained Pruning Reconfigurable dataflow optimization for spatiotemporal spiking neural computation on systolic array accelerators,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:45:58.754937Z

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Observation 9c602406-9b81-4227-966a-6b6f6aa76e4d · outbound

This paper cites Parallel time batching: Systolic-array acceleration of sparse spiking neural computation,.

Bishop: Sparsified Bundling Spiking Transformers on Heterogeneous Cores with Error-Constrained Pruning Parallel time batching: Systolic-array acceleration of sparse spiking neural computation,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:45:58.743819Z

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Observation 980f5bbf-a9c9-47c9-acbb-53bc76028aea · outbound

This paper cites Converting Artificial Neural Networks to Spiking Neural Networks via Parameter Calibration.

Bishop: Sparsified Bundling Spiking Transformers on Heterogeneous Cores with Error-Constrained Pruning Converting Artificial Neural Networks to Spiking Neural Networks via Parameter Calibration

Reference 28

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Observation f263c969-e2a5-4844-aa3d-c7757b70e5b8 · outbound

This paper cites Differentiable spike: Rethink- ing gradient-descent for training spiking neural networks,.

Bishop: Sparsified Bundling Spiking Transformers on Heterogeneous Cores with Error-Constrained Pruning Differentiable spike: Rethink- ing gradient-descent for training spiking neural networks,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:45:58.732778Z

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Observation 3bf163a0-6cd1-47b8-a439-0f3e77bf25c1 · outbound

This paper cites H2learn: High-efficiency learning accelerator for high-accuracy spiking neural networks,.

Bishop: Sparsified Bundling Spiking Transformers on Heterogeneous Cores with Error-Constrained Pruning H2learn: High-efficiency learning accelerator for high-accuracy spiking neural networks,

Reference 30

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Observation 20fb5b14-c1e2-4d84-8f9e-d2655be8a293 · outbound

This paper cites Activen: A scalable and flexibly- programmable event-driven neuromorphic processor,.

Bishop: Sparsified Bundling Spiking Transformers on Heterogeneous Cores with Error-Constrained Pruning Activen: A scalable and flexibly- programmable event-driven neuromorphic processor,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:45:58.710958Z

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Observation 3a0659ed-0570-4892-abac-364ac8f2cd6c · outbound

This paper cites 30.2 a 22nm 0.26 nw/synapse spike-driven spiking neural network processing unit using time-step-first dataflow and sparsity-adaptive in-memory computing,.

Bishop: Sparsified Bundling Spiking Transformers on Heterogeneous Cores with Error-Constrained Pruning 30.2 a 22nm 0.26 nw/synapse spike-driven spiking neural network processing unit using time-step-first dataflow and sparsity-adaptive in-memory computing,

Reference 32

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Observation 2d8b5eca-ce1b-41c4-bd66-d1946429a0bb · outbound

This paper cites Sanger: A co-design framework for enabling sparse attention using reconfigurable architecture,.

Bishop: Sparsified Bundling Spiking Transformers on Heterogeneous Cores with Error-Constrained Pruning Sanger: A co-design framework for enabling sparse attention using reconfigurable architecture,

Reference 33

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Observation 6ef3d52d-be05-4265-be49-4f10cb0ff08b · outbound

This paper cites Networks of spiking neurons: The third generation of neural network models,.

Bishop: Sparsified Bundling Spiking Transformers on Heterogeneous Cores with Error-Constrained Pruning Networks of spiking neurons: The third generation of neural network models,

Reference 34

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Observation dee11b44-613a-452d-9d01-47baa3d825e2 · outbound

This paper cites Stellar: Energy-efficient and low- latency snn algorithm and hardware co-design with spatiotemporal computation,.

Bishop: Sparsified Bundling Spiking Transformers on Heterogeneous Cores with Error-Constrained Pruning Stellar: Energy-efficient and low- latency snn algorithm and hardware co-design with spatiotemporal computation,

Reference 35

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Observation 9999cb16-e627-441d-b864-850e48ca56c3 · outbound

This paper cites Stonne: Enabling cycle-level microarchitectural simulation for dnn inference accelerators,.

Bishop: Sparsified Bundling Spiking Transformers on Heterogeneous Cores with Error-Constrained Pruning Stonne: Enabling cycle-level microarchitectural simulation for dnn inference accelerators,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:45:58.654839Z

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Observation e489be02-c732-44e8-aa0b-f74314635642 · outbound

This paper cites Spinalflow: An architecture and dataflow tailored for spiking neural networks,.

Bishop: Sparsified Bundling Spiking Transformers on Heterogeneous Cores with Error-Constrained Pruning Spinalflow: An architecture and dataflow tailored for spiking neural networks,

Reference 37

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Observation 2083513e-72e4-4932-bd99-08901071ff2f · outbound

This paper cites SIGMA: A sparse and irregular GEMM accelerator with flexible interconnects for DNN training,.

Bishop: Sparsified Bundling Spiking Transformers on Heterogeneous Cores with Error-Constrained Pruning SIGMA: A sparse and irregular GEMM accelerator with flexible interconnects for DNN training,

Reference 38

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Observation 29b93644-4b3e-426a-a95a-03f01cd96888 · outbound

This paper cites DOTA: detect and omit weak attentions for scalable transformer acceleration,.

Bishop: Sparsified Bundling Spiking Transformers on Heterogeneous Cores with Error-Constrained Pruning DOTA: detect and omit weak attentions for scalable transformer acceleration,

Reference 39

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Observation 4f40d2a1-b0f7-401d-9da1-d5754ddd4615 · outbound

This paper cites Stdp-based pruning of connections and weight quantization in spiking neural networks for energy-efficient recognition,.

Bishop: Sparsified Bundling Spiking Transformers on Heterogeneous Cores with Error-Constrained Pruning Stdp-based pruning of connections and weight quantization in spiking neural networks for energy-efficient recognition,

Reference 40

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Observation 246d6286-bb95-4b5c-b8d5-abf9746dcffd · outbound

This paper cites Diet-snn: A low-latency spiking neural network with direct input encoding and leakage and threshold optimization,.

Bishop: Sparsified Bundling Spiking Transformers on Heterogeneous Cores with Error-Constrained Pruning Diet-snn: A low-latency spiking neural network with direct input encoding and leakage and threshold optimization,

Reference 41

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Observation 0f76128e-cc6e-49eb-b7f0-2fd09ac1af82 · outbound

This paper cites Enabling Deep Spiking Neural Networks with Hybrid Conversion and Spike Timing Dependent Backpropagation.

Bishop: Sparsified Bundling Spiking Transformers on Heterogeneous Cores with Error-Constrained Pruning Enabling Deep Spiking Neural Networks with Hybrid Conversion and Spike Timing Dependent Backpropagation

Reference 42

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Observation ae29366c-918d-4819-835a-b1df4f285b01 · outbound

This paper cites Towards spike-based machine intelligence with neuromorphic computing,.

Bishop: Sparsified Bundling Spiking Transformers on Heterogeneous Cores with Error-Constrained Pruning Towards spike-based machine intelligence with neuromorphic computing,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:45:58.621920Z

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Observation a0882bc5-7996-41e4-b019-601250ef9ddc · outbound

This paper cites Towards spike-based machine intelligence with neuromorphic computing,.

Bishop: Sparsified Bundling Spiking Transformers on Heterogeneous Cores with Error-Constrained Pruning Towards spike-based machine intelligence with neuromorphic computing,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:45:58.611139Z

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Observation 19a05371-7322-4cf6-8ec4-654be4519979 · outbound

This paper cites Going deeper in spiking neural networks: Vgg and residual architectures,.

Bishop: Sparsified Bundling Spiking Transformers on Heterogeneous Cores with Error-Constrained Pruning Going deeper in spiking neural networks: Vgg and residual architectures,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:45:58.599914Z

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Observation b2ec89b5-2c2d-4e39-b8dc-8666e9641574 · outbound

This paper cites Nebula: A neuromorphic spin-based ultra-low power architecture for snns and anns,.

Bishop: Sparsified Bundling Spiking Transformers on Heterogeneous Cores with Error-Constrained Pruning Nebula: A neuromorphic spin-based ultra-low power architecture for snns and anns,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:45:58.588060Z

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Observation 92d6ff0f-4cb6-4fc9-a86d-a9a49d351f42 · outbound

This paper cites Skipper: Enabling efficient snn training through activation- checkpointing and time-skipping,.

Bishop: Sparsified Bundling Spiking Transformers on Heterogeneous Cores with Error-Constrained Pruning Skipper: Enabling efficient snn training through activation- checkpointing and time-skipping,

Reference 47

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Observation 7400fdd7-cab9-419f-89ea-1aa28ac8b82c · outbound

This paper cites Spatten: Efficient sparse attention architecture with cascade token and head pruning,.

Bishop: Sparsified Bundling Spiking Transformers on Heterogeneous Cores with Error-Constrained Pruning Spatten: Efficient sparse attention architecture with cascade token and head pruning,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:45:58.576661Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation d7bb2759-5a67-44e4-a24a-5c44c4ae4ab9 · outbound

This paper cites Masked spiking trans- former,.

Bishop: Sparsified Bundling Spiking Transformers on Heterogeneous Cores with Error-Constrained Pruning Masked spiking trans- former,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:45:58.565946Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 30fa9d99-41ec-4901-a58a-0e7b18fa744a · outbound

This paper cites Speech Commands: A Dataset for Limited-Vocabulary Speech Recognition.

Bishop: Sparsified Bundling Spiking Transformers on Heterogeneous Cores with Error-Constrained Pruning Speech Commands: A Dataset for Limited-Vocabulary Speech Recognition

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-15T20:45:57.668411Z

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Unavailable: canonical work link unavailable.

Observation f485f523-0be9-4d45-9a2f-21a0881b06c9 · outbound

This paper cites Spiking transformer hardware accelerators in 3d integration,.

Bishop: Sparsified Bundling Spiking Transformers on Heterogeneous Cores with Error-Constrained Pruning Spiking transformer hardware accelerators in 3d integration,

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:45:58.554867Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 0e51b3f9-8def-461b-a19b-7225248a3cd7 · outbound

This paper cites Deep residual spiking neural network for keyword spotting in low-resource settings.

Bishop: Sparsified Bundling Spiking Transformers on Heterogeneous Cores with Error-Constrained Pruning Deep residual spiking neural network for keyword spotting in low-resource settings

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:45:58.543706Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 465973bd-f05d-4880-99b2-95a219481ba4 · outbound

This paper cites Spike-driven Transformer V2: Meta Spiking Neural Network Architecture Inspiring the Design of Next-generation Neuromorphic Chips.

Bishop: Sparsified Bundling Spiking Transformers on Heterogeneous Cores with Error-Constrained Pruning Spike-driven Transformer V2: Meta Spiking Neural Network Architecture Inspiring the Design of Next-generation Neuromorphic Chips

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-15T20:45:57.679503Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 944b6ac4-462c-49a0-87f1-c7d80078ce88 · outbound

This paper cites Spike-driven Transformer.

Bishop: Sparsified Bundling Spiking Transformers on Heterogeneous Cores with Error-Constrained Pruning Spike-driven Transformer

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-15T20:45:57.683368Z

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Unavailable: canonical work link unavailable.

Observation 33050ec5-9d9a-4abc-8c4c-32d5f092e9f5 · outbound

This paper cites Loas: Fully temporal-parallel dataflow for dual-sparse spiking neural networks,.

Bishop: Sparsified Bundling Spiking Transformers on Heterogeneous Cores with Error-Constrained Pruning Loas: Fully temporal-parallel dataflow for dual-sparse spiking neural networks,

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:45:58.532506Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 4ccc08fa-6f51-4c77-9128-2a2a11faf76c · outbound

This paper cites Mint: Multiplier-less integer quantization for energy efficient spiking neural networks,.

Bishop: Sparsified Bundling Spiking Transformers on Heterogeneous Cores with Error-Constrained Pruning Mint: Multiplier-less integer quantization for energy efficient spiking neural networks,

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:45:58.521450Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation fc36dd30-4851-49ff-b5f6-fcc3b109741f · outbound

This paper cites Sata: Sparsity-aware training accelerator for spiking neural networks,.

Bishop: Sparsified Bundling Spiking Transformers on Heterogeneous Cores with Error-Constrained Pruning Sata: Sparsity-aware training accelerator for spiking neural networks,

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:45:58.510138Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 413b809c-6c7a-4cc0-9108-3957da0a3091 · outbound

This paper cites Vitcod: Vision transformer acceleration via dedicated algorithm and accelerator co-design,.

Bishop: Sparsified Bundling Spiking Transformers on Heterogeneous Cores with Error-Constrained Pruning Vitcod: Vision transformer acceleration via dedicated algorithm and accelerator co-design,

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-15T20:45:57.697217Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 319b883a-b074-4eda-9820-111bd1c5a8e4 · outbound

This paper cites Castling-ViT: Compressing self-attention via switching towards linear-angular attention at vision transformer inference,.

Bishop: Sparsified Bundling Spiking Transformers on Heterogeneous Cores with Error-Constrained Pruning Castling-ViT: Compressing self-attention via switching towards linear-angular attention at vision transformer inference,

Reference 59

Resolution: verified exact; raw_fallback, observed 2026-08-15T20:45:57.890891Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 4582b427-7152-4c5d-a3d8-4b719e3d9452 · outbound

This paper cites Spiking transformers for event-based single object tracking,.

Bishop: Sparsified Bundling Spiking Transformers on Heterogeneous Cores with Error-Constrained Pruning Spiking transformers for event-based single object tracking,

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:45:58.497708Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 1fdf19ef-b093-49de-b319-4cbef6efd262 · outbound

This paper cites Temporal spike sequence learning via backpropagation for deep spiking neural networks,.

Bishop: Sparsified Bundling Spiking Transformers on Heterogeneous Cores with Error-Constrained Pruning Temporal spike sequence learning via backpropagation for deep spiking neural networks,

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:45:58.485798Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation afba4dc7-569b-4259-be27-95749abb3e94 · outbound

This paper cites ALISA: Accelerating Large Language Model Inference via Sparsity-Aware KV Caching.

Bishop: Sparsified Bundling Spiking Transformers on Heterogeneous Cores with Error-Constrained Pruning ALISA: Accelerating Large Language Model Inference via Sparsity-Aware KV Caching

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-15T20:45:57.712775Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 74a0bcc1-e17b-40b7-8658-9fda02e24a53 · outbound

This paper cites Going deeper with directly-trained larger spiking neural networks,.

Bishop: Sparsified Bundling Spiking Transformers on Heterogeneous Cores with Error-Constrained Pruning Going deeper with directly-trained larger spiking neural networks,

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:45:58.474251Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation d9218ae9-9cac-42eb-8640-25f0475e2276 · outbound

This paper cites Spikformer: When spiking neural network meets transformer,.

Bishop: Sparsified Bundling Spiking Transformers on Heterogeneous Cores with Error-Constrained Pruning Spikformer: When spiking neural network meets transformer,

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:45:58.461328Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 3be9b20a-0763-4f1b-9228-93995fa8014f · outbound

This paper cites Spikegpt: Generative pre-trained language model with spiking neural networks,.

Bishop: Sparsified Bundling Spiking Transformers on Heterogeneous Cores with Error-Constrained Pruning Spikegpt: Generative pre-trained language model with spiking neural networks,

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:45:58.449324Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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